李宏毅2021/2022/2023春季机器学习课程课件及作业

Official repository of TwiBot-22 @ NeurIPS 2022, Datasets and Benchmarks Track.

这是一个简单的技术科普教程项目，主要聚焦于解释一些有趣的，前沿的技术概念和原理。每篇文章都力求在 5 分钟内阅读完成。

This repository collects debiasing methods for recommendation

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

The definitive Web UI for local AI, with powerful features and easy setup.

SeBot: Structural Entropy Guided Multi-View Contrastive learning for Social Bot Detection. KDD 2024

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

A Python library used to collect shilling detection methods and generate simulated attackers. (for academic use)

Multi-scale Information Diffusion Prediction with Sequential Hypergraphs

[NeurIPS 2024] An official source code for paper "End-to-end Learnable Clustering for Intent Learning in Recommendation".

A unified, comprehensive and efficient recommendation library

The relevant codes for "GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections".

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

This repository contains our implementations for Shilling Attacks against Recommender Systems.

An open-source framework for conducting data poisoning attacks on recommendation systems, designed to assist researchers and practitioners.

source code for "Planning Data Poisoning Attacks on Heterogeneous Recommender Systems in a Multiplayer Setting" to appear ICDE 2023

Source Code for CIKM'23 paper "Single-User Injection for Invisible Shilling Attack against Recommender Systems".

Adversarial attacks and defenses on Graph Neural Networks.

A Survey of Poisoning Attacks and Defenses in Recommender Systems

[KDD'21] Official PyTorch implementation for "Data Poisoning Attack against Recommender System Using Incomplete and Perturbed Data".

Survey on the recommendation attack topic, continuing to update.

Deep and conventional community detection related papers, implementations, datasets, and tools.

Implementation of paper "Explanability-based backdoor attacks against graph neural networks"

Implementation of XGBD: Explanation-Guided Backdoor Detection on Graphs